Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
2,837
datasets available to search
ShareScore release 0.9.0
Dataset results
2,837 results for “Climate Data”
Supporting data for Tebaldi et al. 2021 - Nature Climate Change
<p>This is the dataset underpinning the paper "Extreme Sea Levels at Different Global Warming Levels" accepted in Nature Climate Change in 2021. Information about the paper as well as the supporting code used to process and analyze the data can be found at: https://github.com/DOE-ICoM/tebaldi-etal_2021_natclimchange.</p>
Supplementary data: "Future operation of hydropower in Europe under high renewable penetration and climate change"
<p>This dataset contains modelled inflow time series described in the paper "Future operation of hydropower in Europe<br> under high renewable penetration and climate change".</p> <p>The inflow is derived from ten different combinations of five General Circulation Models and two Regional Climate Models at the beginning of the century ("Hydro_inflow_BOC_(...).csv"), 1991 - 2020, and at the end of the century ("Hydro_inflow_EOC_(...).csv"), 2071 - 2100, under three CO2-emissions scenarios (RCP2.6, RCP4.5, and RCP8.5). The ensemble mean for each emissions scenario is presented as well.</p> <p>The historical data that is not confidential is given as well. See "data_sources" for sources.</p>
Ocean and ice with waves data for role of surface gravity waves in aquaplanet ocean climates
<p>This data corresponds to the runs analysed in the manscript: Role of Surface Gravity Waves in Aquaplanet Ocean Climates (JAMES, 2021).</p> <p>In this work, we present a set of idealised numerical experiments that demonstrate the thermodynamic and dynamic implications of surface gravity waves for the oceanic climate of an aquaplanet. We study the impact of accounting for modulations by such waves upon air-sea momentum fluxes, Langmuir circulation and the Stokes-Coriolis force.</p> <p>This dataset is made up of atmospheric, oceanic and surface gravity wave simulations. When uncompressed the total dataset is 1.6 TB, the ocean and ice with waves component is 564 GB. See below for further details.</p> <p>See the related works section for the corresponding datasets.</p>
Ocean and ice without waves data for role of surface gravity waves in aquaplanet ocean climates
<p>This data corresponds to the runs analysed in the manscript: Role of Surface Gravity Waves in Aquaplanet Ocean Climates (JAMES, 2021).</p> <p>In this work, we present a set of idealised numerical experiments that demonstrate the thermodynamic and dynamic implications of surface gravity waves for the oceanic climate of an aquaplanet. We study the impact of accounting for modulations by such waves upon air-sea momentum fluxes, Langmuir circulation and the Stokes-Coriolis force.</p> <p>This dataset is made up of atmospheric, oceanic and surface gravity wave simulations. When uncompressed the total dataset is 1.6 TB, the ocean and ice without waves component is 484 GB. See below for further details.</p> <p>See the related works section for the corresponding datasets.</p>
Upslope migration of snow avalanches in a warming climate: data and model source files
<p>Complete data and model source files corresponding to:</p> <p>Giacona, F., Eckert, N., Corona, C., Mainieri, R., Morin, S., Stoffel, M., Martin, B., Naaim, M. (2021). Upslope migration of snow avalanches in a warming climate. Proceedings of the National Academy of Sciences America, Nov 2021, 118 (44) e2107306118; DOI: 10.1073/pnas.2107306118</p>
Mirror of data from NOAA U.S. Climate Reference Network for Research Computing in Earth Science
<p>This is a mirror of data from the NOAA U.S. Climate Reference Network (https://www.ncei.noaa.gov/products/land-based-station/us-climate-reference-network).</p> <p>It was created because outbound FTP access is not allowed from some cloud-based JupyterHub setups.</p>
Daily maximum VPD - supporting data for Jain et al. 2021, Nature Climate Change
<p>Global daily maximum Vapour Pressure Deficit (VPD) for 1979-2020 at 0.25 deg resolution. This data supports the analysis in "Observed increases in extreme fire weather driven by atmospheric humidity and temperature", Jain et al. 2021, accepted for publication in Nature Climate Change.</p> <p>VPD was calculated using the hourly ERA5 2m temperature and 2m dewpoint temperature using the Alduchov and Eskridge (1996) approximation as implemented in the R package ‘bigleaf’ (Knauer et al. 2018).</p> <p>Variables were processed using inputs from the ERA5 Reanalysis (hourly surface data from 1979–2020, available from <a href="https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview">https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview</a>). </p> <p>References</p> <p>Alduchov, O. A. & Eskridge, R. E., 1996: Improved Magnus form approximation of saturation vapor pressure. Journal of Applied Meteorology, 35, 601-609</p> <p>Knauer, J., El-Madany, T. S., Zaehle, S., & Migliavacca, M. (2018). Bigleaf—An R package for the calculation of physical and physiological ecosystem properties from eddy covariance data. <em>PloS one</em>, <em>13</em>(8), e0201114.</p> <p> </p> <p> </p>
Data from: Fertiliser application modulates the impact of interannual climate fluctuations and plant-to-plant interactions on the dynamics of annual species in a Mediterranean grassland
<p><span><strong><span>Background:</span></strong><span> Climate and land-use changes, which include the application of various types of organic and inorganic fertilisers, have been reducing the species diversity of Mediterranean grasslands and threatening their conservation. Annual plants are one of the most diverse functional groups of species in these grasslands, despite suffering competitive pressure from perennial herbaceous and woody species, and they are essential for ecosystem functioning and stability. </span></span></p> <p><span><strong><span>Aims:</span></strong><span> To quantify how fertilisation modulates the impact of plant-to-plant interactions and climate fluctuations on the dynamics of annuals in Mediterranean grasslands. We hypothesised that the application of sewage sludge would increase competition between functional groups, reducing the abundance of annuals in the long-term, but would buffer the negative impacts of drought on the year-to-year fluctuation of the diversity of annuals.</span></span></p> <p><span><strong><span>Methods:</span></strong><span> In a semi-natural species-rich Mediterranean grassland in northern Spain, we analysed the changes in the taxonomical and functional composition and diversity of annuals over 14 years in response to variations in the abundance of perennial herbaceous and woody species, climate fluctuations, and fertilisation with sewage sludge. We quantified separately the patterns of year-to-year fluctuations and long-term trends. </span></span></p> <p><span><strong><span>Results:</span></strong><span> The frequency and diversity of annuals decreased with a higher abundance of perennial herbaceous species, drought in June, and cold winters. The addition of sewage sludge decreased the abundance of annuals in the long-term, seemed to promote competition between annuals and other functional groups at an interannual scale, and mitigated the negative effects of drought and cold.</span></span></p> <p><span><span><strong>Conclusions:</strong> Fertilisation influences differently the temporal response of annuals to climate fluctuations and plant-to-plant interactions.</span></span></p>
Data, code and supplementary material for "A data integration framework for spatial interpolation of temperature observations using climate model data"
<p>Each zipped file contains code and data to reproduce the results in the paper and supplementary material. The Cyprus folder contains also the files to run the model, as well as the associated results. The Morocco folder only contains the results and the code used to manipulate it. </p>
Simulations for pre-industrial climate using EC-Earth3-LR model — selected data for a study on AMOC
<p>A long-term control simulation of pre-industrial period (1850 CE) climates were performed by the EC-Earth3-LR climate model with a horizontal resolution of ~1.125°. The dataset contains selected output data from the simulations.</p> <p>In total, a 2000-year long control simulation was made, which has pre-industrial orbital boundary conditions, initialized by a pre-run steady restart file (the output of approximately 500-year pre-industrial control simulation). This dataset is used to investigate internal climate variability without external forcing changes under pre-industrial climate conditions.</p> <p>The dataset contains Earth system model results from EC-Earth3 presented in the study by Cao et al. (2022).</p> <p><strong>Model configuration</strong><br> Time periods: Pre-Industrial (2000-year time slice)<br> ESM configuration: EC-Earth3-LR<br> Horizontal resolution: ~1.125° (~125 km)</p> <p><strong>Available data</strong><br> Annual mean data for standard oceanographic and meteorological variables.</p>
Data from: Species-specific traits mediate avian demographic responses under past climate change
<p>Anticipating species' responses to environmental change is a<span> pressing mission in biodiversity conservation. Despite decades of research investigating how climate change may affect population sizes, historical context is lacking and the traits which mediate demographic sensitivity to changing climate remain elusive. We use whole-genome sequence data to reconstruct the demographic histories of 263 bird species over the past million years and identify networks of interacting morphological and life-history traits associated with changes in effective population size (<em>N<sub>e</sub></em>) in response to climate warming and cooling. Our results identify direct and indirect effects of key traits representing survival, reproduction, and dispersal processes on long-term demographic responses to climate change and highlight traits most likely to influence population responses to ongoing climate warming.</span></p>
Data for: Four decades of phenology in an alpine amphibian: trends, stasis, and climatic drivers
<p>This dataset is used for the analysis of the breeding phenology of a common toad (<em>Bufo bufo</em>) alpine population, and how it is associated with either climatic conditions or the genetics of the population.</p> <p> </p> <p><strong>Toad Data</strong></p> <p>Since 1982, we have captured annually all the toads that come to breed at the study pond. We then marked (first by toe-clipping, then starting in 1993 by implanting PIT tags), measured, and released them in the same place (Hemelaar, 1988; Grossenbacher, 2002). To make sure we captured both early and late arrivers, we repeated this procedure for on average 5–6 nights, with breaks in-between of about 2-4 days (i.e, the data conform to Pollock’s (1982) robust design). The length of the field work period usually covers the breeding season duration, which typically lasts about two weeks at our study pond. This design also had the advantage of not overly stressing the toads. In total, for the period 1982–2020, 3053 uniquely recognizable individuals have been caught, of which 1852 were males and 1201 females. For each individual we have a record of presence for each capture night over the study period. Given the reduced size of the pond and the repeated capture rounds within a capture night, we assumed high capture probabilities (capture probability p ≈ 0.85 per year based on a preliminary analysis of the mark-recapture data). At the population level we determined for each year a start, a peak, and an end date of breeding (i.e., first capture night, the capture night when most toads were captured, and last capture night, respectively). These calendar dates were all transformed into days of the year (where January 1<sup>st</sup> is 1), to facilitate modelling of long-term trends.</p> <p> </p> <p><strong>Weather Data</strong></p> <p>We obtained climatic data for the period 1980–2020 from the DaymetCH dataset (data obtained from Bioclimatic maps of Switzerland © WSL, based on station data from the Federal Office of Meteorology and Climatology MeteoSwiss, and elaborated by the Land Change Science group, WSL). This dataset consists of a 100-metre resolution grid of interpolated estimates of weather variables, using meteorological data from ground stations and the Daymet software (Thornton et al., 1997). We obtained data for the cell containing the breeding pond for the following variables: daily minimum, maximum, and mean temperature, daily total precipitation, and daily snow water equivalent (SWE; the equivalent amount of water stored in the snow pack). We then calculated average seasonal minimum daily temperatures (winter and spring), and cumulative seasonal precipitation (spring) and SWE (winter and spring). The csv file Season_values store these measures (one value for each of the 5 climatic variables per year, for the period 1982-2020, as the study on the toads started in 1982).</p> <p>We conducted all the analyses in R (R version 4.1.1; R Core Team, 2020) with RStudio (version 2022.7.1.554; R Studio Team, 2022).</p>
Data from: Earlier flowering of winter oilseed rape compensates for higher pest pressure in warmer climates
<p>Pest abundance and timing of migration relative to the vulnerable crop stage influence the severity of crop damage and yield loss to insect pests in oilseed rape (OSR). Both abundance and timing are influenced by landscape composition, changes therein due to crop rotation, and temperature. The need for sustainable and temperature-adapted management strategies of OSR pests due to the environmental harm of current conventional practices and global warming calls for a better understanding of the combined effects of landscape composition and temperature on pest abundances, larval parasitism, crop damage and yield, but also of the role of crop phenology for crop damage and yield under field conditions. Here, 29 winter OSR crops were studied along a multi-annual mean temperature gradient (MAT, 1981–2010) in Bavaria, Germany. We measured pest abundances (pollen beetles, stem weevils), crop damage (bud loss, stem tunnelling), pollen beetle larval parasitism and crop yield and calculated Julian dates of flowering from biweekly observations of growth stages. Pest abundances and parasitism were analysed with regard to MAT and landscape parameters at six scales (non-crop habitat and OSR area, change in the proportion of OSR area relative to the previous year; 0.6 km, and 1–5 km in 1-km steps), while analysis of crop damage and yield also included Julian date of flowering. Pollen beetle abundance was increased under higher MAT, but less strongly when OSR proportions were high (1-km scale) and not strongly reduced relative to the previous year (5-km scale), while pollen beetle larval parasitism was overall low but exceeded 30% (considered as threshold for effective natural control) occasionally under both low and high MAT. In contrast to abundance of adult pollen beetles, stem weevil larval abundance – as well as stem damage – did not respond to landscape composition nor MAT. Despite high abundance of adult pollen beetles under high MAT, crop yield was high (and the proportion of bud loss low) under high MAT when OSR flowered early. Our results underpin the potential of targeted landscape management (e.g. through regionally coordinated crop rotations) and timing of flowering (e.g. through cultivar choice) for environment-friendly and temperature-adapted pest management in winter OSR.</p>
Genomic data and common garden experiments reveal climate-driven selection on ecophysiological traits in two Mediterranean oaks
<p>This release includes the different genomic datasets used in the article entitled "<em>Genomic data and common garden experiments reveal climate-driven selection on ecophysiological traits in two Mediterranean oaks</em> " by Ramírez-Valiente et al.,</p> <p>File description:</p> <p><strong>Samples.xlsx</strong>: Description of individual and population codes used in the different analyses and genomic datasets.</p> <p><strong>Quercus_faginea_p12r05m05minMAF001_all_loci.str</strong>: Input file used to perform genetic clustering analyses (STRUCTURE and DAPC) for <em>Quercus faginea</em> including all loci.</p> <p><strong>Quercus_faginea_p12r05m05minMAF001_neutral_loci.str</strong>: Input file used to perform genetic clustering analyses (STRUCTURE and DAPC) for <em>Quercus faginea</em> excluding outlier loci (i.e., putatively under selection) identified by either BAYESCAN or using the FDIST method in ARLEQUIN.</p> <p><strong>Quercus_lusitanica_p7r05m05minMAF001_all_loci.str</strong>: Input file used to perform genetic clustering analyses (STRUCTURE and DAPC) for <em>Quercus lusitanica </em>including all loci.</p> <p><strong>Quercus_ lusitanica_p7r05m05minMAF001_neutral_loci.str</strong>: Input file used to perform genetic clustering analyses (STRUCTURE and DAPC) for <em>Quercus lusitanica </em>excluding outlier loci (i.e., putatively under selection) identified by either BAYESCAN or using the FDIST method in ARLEQUIN.</p> <p><strong>Quercus_faginea_p12r05m05minMAF001_BAYESCAN.txt</strong>: Input file used to perform BAYESCAN analyses for <em>Quercus faginea</em>.</p> <p><strong>Quercus_lusitanica_p7r05m05minMAF001_BAYESCAN.txt</strong>: Input file used to perform BAYESCAN analyses for <em>Quercus lusitanica</em>.</p> <p><strong>Quercus_faginea_p12r05m05minMAF001_ARLEQUIN.arp</strong>: Input file used to perform ARLEQUIN analyses for <em>Quercus faginea</em>.</p> <p><strong>Quercus_lusitanica_p7r05m05minMAF001_ARLEQUIN.arp</strong>: Input file used to perform ARLEQUIN analyses for <em>Quercus lusitanica</em>.</p> <p><strong>Quercus_faginea_p12r05m05minMAF001_all_loci.vcf</strong>: Variant call format (VCF) file for <em>Quercus faginea</em> including all loci.</p> <p><strong>Quercus_faginea_p12r05m05minMAF001_neutral_loci.vcf</strong>: Variant call format (VCF) file for <em>Quercus faginea</em> excluding outlier loci (i.e., putatively under selection) identified by either BAYESCAN or using the FDIST method in ARLEQUIN.</p> <p><strong>Quercus_lusitanica_p7r05m05minMAF001_all_loci.vcf</strong>: Variant call format (VCF) file for <em>Quercus lusitanica </em>including all loci.</p> <p><strong>Quercus_ lusitanica_p7r05m05minMAF001_neutral_loci.vcf</strong>: Variant call format (VCF) file for <em>Quercus lusitanica </em>excluding outlier loci (i.e., putatively under selection) identified by either BAYESCAN or using the FDIST method in ARLEQUIN.</p> <p><strong>Quercus_faginea_Greenhouse_DRIFTSEL.txt</strong>: Input file used to run DRIFTSEL and evaluate selection on the different studied traits for <em>Quercus faginea </em>under common garden greenhouse experiments.</p> <p><strong>Quercus_faginea_Outdoor_DRIFTSEL.txt</strong>: Input file used to run DRIFTSEL and evaluate selection on the different studied traits for <em>Quercus faginea</em> under common garden outdoor experiments.</p> <p><strong>Quercus_lusitanica_Greenhouse_DRIFTSEL.txt</strong>: Input file used to run DRIFTSEL and evaluate selection on the different studied traits for <em>Quercus lusitanica </em>under common garden greenhouse experiments.</p>
Bias-corrected data from the preoperational MiKlip system for decadal climate predictions used in the PNRA-IPSODES project
<p>This dataset contains a selection of bias-corrected data from the preoperational MiKlip system for decadal climate predictions (Mueller et al., 2018) used within the Italian research project PNRA18_00199-IPSODES. The adopted method for bias correction is described in the file bias_correction.pdf. Also data from the assimilation run are provided. Nomenclature of variables follows that of the original MiKlip output.</p> <p>Mueller, W., et al. A Higher‐resolution Version of the Max Planck Institute Earth System Model (MPI‐ESM1.2‐HR). J. Adv. Model. Earth Syst. 10, 1383-1413 (2018)</p>
Data for: Predicting habitat suitability for Townsend's big-eared bats across California in relation to climate change
<p>Aim: Effective management decisions depend on knowledge of species distribution and habitat use. Maps generated from species distribution models are important in predicting previously unknown occurrences of protected species. However, if populations are seasonally dynamic or locally adapted, failing to consider population level differences could lead to erroneous determinations of occurrence probability and ineffective management. The study goal was to model the distribution of a species of special concern, Townsend's big-eared bats (Corynorhinus townsendii), in California. We incorporate seasonal and spatial differences to estimate the distribution under current and future climate conditions.</p> <p>Methods: We built species distribution models using all records from statewide roost surveys and by subsetting data to seasonal colonies, representing different phenological stages, and to Environmental Protection Agency Level III Ecoregions to understand how environmental needs vary based on these factors. We projected species' distribution for 2061-2080 in response to low and high emissions scenarios and calculated the expected range shifts.</p> <p>Results: The estimated distribution differed between the combined (full dataset) and phenologically-explicit models, while ecoregion-specific models were largely congruent with the combined model. Across the majority of models, precipitation was the most important variable predicting the presence of C. townsendii roosts. Under future climate scnearios, distribution of C. townsendii is expected to contract throughout the state, however suitable areas will expand within some ecoregions. Main conclusion: Comparison of phenologically-explicit models with combined models indicate the combined models better predict the extent of the known range of C. townsendii in California. However, life history-explicit models aid in understanding of different environmental needs and distribution of their major phenological stages. Differences between ecoregion-specific and statewide predictions of habitat contractions highlight the need to consider regional variation when forecasting species' responses to climate change. These models can aid in directing seasonally explicit surveys and predicting regions most vulnerable under future climate conditions.</p>
Highly consistent brightness temperature fundamental climate data record from SSM/I and SSMIS
<p>The highly consistent brightness temperature (TB) fundamental climate data record (FCDR) comprises intercalibrated TBs from SSM/I on F11 and F13, and SSMIS on board F17. It covers the time period from December 1991 to December 2021. It provides homogenized and intercalibrated TBs in a user-friendly data format (HDF5). SSM/I and SSMIS data are used for various applications, such as analyses of the hydrological cycle. The improved homogenization and inter-calibration procedure ensure the long-term stability of the FCDR for climate related applications. <br> This data files contain daily TBs data on 1°×1° grid-level of satellite F11, F13 and F17 (Level 2A).<br> It is worth noting that the original sensor TB data are provided by Level-1C dataset. The Level-1C data record is complemented with scan status, quality flags, sun glint angles, and earth incidence angles.</p>
High-resolution tropical rain-forest canopy climate data
<p><span>Canopy habitats challenge researchers with their intrinsically difficult access. The current scarcity of climatic data from forest canopies limits our understanding of the conditions and environmental variability of these diverse and dynamic habitats. We present 307 days of climate records collected between 2019 and 2020 in the tropical rainforest canopy of the Yasuní National Park, Ecuador. We monitored climate with a 10-minute temporal resolution in the middle crowns of eight canopy trees. The distance between canopy climate stations ranged from 700 m to 10 km. Apart from air temperature, relative humidity, leaf wetness, and photosynthetically active radiation (PAR), measured in each canopy climate station, global radiation, rainfall, and wind speed were measured in different subsets of them. We processed the eight data series to omit erroneous records resulting from sensor failures or lack of the solar-based power supply. In addition to the eight original data series, we present three derived data series, two aggregating canopy climate for valleys or for ridges (from four stations each), and one overall average (from the eight stations). This last derived data series contains 306 days, while the shortest of the original data series covers 22 days and the longest 296 days. In addition to the data, two open-source tools, developed in RStudio, are presented that facilitate data visualization (a dashboard) and data exploration (a filtering app) of the original and aggregated records.</span></p>
Data for: Genomic vulnerability to climate change in Quercus acutissima, a dominant tree species in East Asian deciduous forests
<p><span>Understanding the evolutionary processes that shape the landscape of genetic variation and influence the response of species to future climate change is critical for biodiversity conservation. Here, we sampled </span><span>27</span><span> populations across the distribution range of a dominant forest tree, <em>Quercus</em> <em>acutissima</em>, in East Asia, and applied genome-wide analyses to track the evolutionary history and predict the fate of populations under future climate. We found two genetic groups (East and West) in <em>Q</em>. <em>acutissima</em> that diverged during the Pliocene. </span><span>We also found</span><span> a heterogeneous landscape of genomic variation in this species</span><span>, which may have been shaped by </span><span>population demography and </span><span>linked selections</span><span>.</span><span> Using genotype-environment association analyses, we identified climate-associated SNPs in a diverse set of genes and functional categories, indicating a model of polygenic adaptation in <em>Q</em>. acutissima<em>.</em> We further estimated three genetic offset metrics to quantify genomic vulnerability of this species to climate change due to the complex interplay </span><span>between</span><span> local adaptation</span><span> and</span><span> migration</span><span>.</span><span> We found that marginal populations are under </span><span>higher</span><span> risk of local extinction</span><span> because of</span><span> future climate change</span><span>, and may not be able to track </span><span>suitable habitats </span><span>to maintain the gene-environment relationships observed under the current climate.</span><span> We also detected higher reverse genetic offsets in northern China, indicating that genetic variation currently present in the whole range of <em>Q</em>. <em>acutissima</em> may not adapt to future climate conditions in this area.</span> <span>Overall, this study</span><span> illustrates how evolutionary</span><span> processes </span><span>have</span><span> shaped the landscape of genomic variation, and</span><span> provides a comprehensive genome-wide view of climate maladaptation in <em>Q</em>. <em>acutissima</em>.</span></p>
Supplementary Data and Code: Determinants of range sizes pinpoint vulnerability of groundwater species to climate change: a case study on subterranean amphipods from the Dinarides
<p>Supplementary Data and R code for phylogenetic analyses for manuscript entitled <em>Determinants of range sizes pinpoint vulnerability of groundwater species to climate change: a case study on subterranean amphipods from the Dinarides.</em></p> <p><strong>The dataset contains</strong></p> <p><em>beast.tree</em> → data for import into R: maximum credibility phylogeny<br> <em>data_lambert.csv</em> → data for import into R: data on habitat and distribution for 52 <em>Niphargus </em>species<br> <em>morpho.csv</em> → data for import into R: morphometric data (body length) for 52 <em>Niphargus </em>species<br> <em>niphargus_ranges.Rmd</em> → fully reproducible R markdown file<br> <em>niphargus_ranges.html </em>→ html output of Rmd file</p> <p>To be able to run the analysis put the data files into folder <data> and run the Rmd script.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.